Active Dendrite Suppression by Ferroelectric Membrane Separators in Rechargeable Batteries.

Anodic dendrite formation is a critical issue in rechargeable batteries and often leads to poor cycling stability and quick capacity loss. Prevailing strategies for dendrite suppression aim at slowing down the growth rate kinetically but still leaving possibilities for dendrite evolution over time. Herein, we report a complete dendrite elimination strategy using a mesoporous ferroelectric polymer membrane as the battery separator. The dendrite suppression is realized by spontaneously reversing the surface energetics for metal ion reduction at the protrusion front, where a positive piezoelectric polarization is generated and superimposed as the protrusion compresses the separator. This effect is demonstrated first in a Zn electroplating process, and further in Zn-Zn symmetric cells and Zn-NaV3O8·1.5H2O full cells, where the dendritic Zn anode surfaces are completely turned into featureless flat surfaces. Consequently, a substantially longer charging/discharging cycle is achieved. This study provides a promising pathway toward high-performance dendrite-free rechargeable batteries.

Recurrent neural network-based simultaneous cardiac T1, T2, and T1ρ mapping.

The purpose of the current study was to explore the feasibility of training a deep neural network to accelerate the process of generating T1, T2, and T1ρ maps for a recently proposed free-breathing cardiac multiparametric mapping technique, where a recurrent neural network (RNN) was utilized to exploit the temporal correlation among the multicontrast images. The RNN-based model was developed for rapid and accurate T1, T2, and T1ρ estimation. Bloch simulation was performed to simulate a dataset of more than 10 million signals and time correspondences with different noise levels for network training. The proposed RNN-based method was compared with a dictionary-matching method and a conventional mapping method to evaluate the model's effectiveness in phantom and in vivo studies at 3 T, respectively. In phantom studies, the RNN-based method and the dictionary-matching method achieved similar accuracy and precision in T1, T2, and T1ρ estimations. In in vivo studies, the estimated T1, T2, and T1ρ values obtained by the two methods achieved similar accuracy and precision for 10 healthy volunteers (T1: 1228.70 ± 53.80 vs. 1228.34 ± 52.91 ms, p > 0.1; T2: 40.70 ± 2.89 vs. 41.19 ± 2.91 ms, p > 0.1; T1ρ: 45.09 ± 4.47 vs. 45.23 ± 4.65 ms, p > 0.1). The RNN-based method can generate cardiac multiparameter quantitative maps simultaneously in just 2 s, achieving 60-fold acceleration compared with the dictionary-matching method. The RNN-accelerated method offers an almost instantaneous approach for reconstructing accurate T1, T2, and T1ρ maps, being much more efficient than the dictionary-matching method for the free-breathing multiparametric cardiac mapping technique, which may pave the way for inline mapping in clinical applications.

Rational Design of Photocatalysts for Controlled Polymerization: Effect of Structures on Photocatalytic Activities.

Over the past decade, the use of photocatalysts (PCs) in controlled polymerization has brought new opportunities in sophisticated macromolecular synthesis. However, the selection of PCs in these systems has been typically based on laborious trial-and-error strategies. To tackle this limitation, computer-guided rational design of PCs based on knowledge of structure-property-performance relationships has emerged. These rational strategies provide rapid and economic methodologies for tuning the performance and functionality of a polymerization system, thus providing further opportunities for polymer science. This review provides an overview of PCs employed in photocontrolled polymerization systems and summarizes their progression from early systems to the current state-of-the-art. Background theories on electronic transitions are also introduced to establish the structure-property-performance relationships from a perspective of quantum chemistry. Typical examples for each type of structure-property relationships are then presented to enlighten future design of PCs for photocontrolled polymerization.

Some Recent Advances in Density-Based Reactivity Theory.

Establishing a chemical reactivity theory in density functional theory (DFT) language has been our intense research interest in the past two decades, exemplified by the determination of steric effect and stereoselectivity, evaluation of electrophilicity and nucleophilicity, identification of strong and weak interactions, and formulation of cooperativity, frustration, and principle of chirality hierarchy. In this Featured Article, we first overview the four density-based frameworks in DFT to appreciate chemical understanding, including conceptual DFT, use of density associated quantities, information-theoretic approach, and orbital-free DFT, and then present a few recent advances of these frameworks as well as new applications from our studies. To that end, we will introduce the relationship among these frameworks, determining the entire spectrum of interactions with Pauli energy derivatives, performing topological analyses with information-theoretic quantities, and extending the density-based frameworks to excited states. Applications to examine physiochemical properties in external electric fields and to evaluate polarizability for proteins and crystals are discussed. A few possible directions for future development are followed, with the special emphasis on its merger with machine learning.

Unified construction of relativistic Hamiltonians.

It is shown that the four-component (4C), quasi-four-component (Q4C), and exact two-component (X2C) relativistic Hartree-Fock equations can be implemented in a unified manner by making use of the atomic nature of the small components of molecular 4-spinors. A model density matrix approximation can first be invoked for the small-component charge/current density functions, which gives rise to a static, pre-molecular mean field to be combined with the one-electron term. As a result, only the nonrelativistic-like two-electron term of the 4C/Q4C/X2C Fock matrix needs to be updated during the iterations. A "one-center small-component" approximation can then be invoked in the evaluation of relativistic integrals, that is, all atom-centered small-component basis functions are regarded as extremely localized near the position of the atom to which they belong such that they have vanishing overlaps with all small- or large-component functions centered at other nuclei. Under these approximations, the 4C, Q4C, and X2C mean-field and many-electron Hamiltonians share precisely the same structure and accuracy. Beyond these is the effective quantum electrodynamics Hamiltonian that can be constructed in the same way. Such approximations lead to errors that are orders of magnitude smaller than other sources of errors (e.g., truncation errors in the one- and many-particle bases as well as uncertainties of experimental measurements) and are, hence, safe to use for whatever purposes. The quaternion forms of the 4C, Q4C, and X2C equations are also presented in the most general way, based on which the corresponding Kramers-restricted open-shell variants are formulated for "high-spin" open-shell systems.

Effects of Continuous Nutritional Intervention on Nutritional Status and Serum Albumin During Maintenance Therapy in Children with Acute Lymphoblastic Leukemia.

Background: Nutritional imbalances can significantly impact clinical efficacy and chemotherapy tolerance in cases of acute lymphoblastic leukemia. Despite the potential significance, there is limited research in this domain, and clinicians have paid limited attention to it. Objective: This study aims to investigate the impact of continuous nutritional intervention on pediatric patients with acute lymphoblastic leukemia. Methods: A comparative analysis was conducted by dividing the children into observation and control groups, examining the effects of intermittent diet intervention and continuous nutrition intervention post-nutritional risk assessment. Results: After the intervention, the observation group exhibited a higher proportion of good nutrition and elevated serum albumin levels compared to the control group (χ2=4.79, 5.49, P = .029, 0.019, t =-2.819, -5.559, P = .01, P < .001). Additionally, the complication rate in the observation group was significantly lower than that in the control group (χ2=5.247, P = .022). Conclusions: Continuous nutrition intervention emerges as a valuable strategy for improving the nutritional status and serum albumin levels in children undergoing maintenance treatment for acute lymphoblastic leukemia. Moreover, it contributes to a noteworthy reduction in the incidence of complications.

Pushing the Limit of Photo-Controlled Polymerization: Hyperchromic and Bathochromic Effects.

The photocatalyst (PC) zinc tetraphenylporphyrin (ZnTPP) is highly efficient for photoinduced electron/energy transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization. However, ZnTPP suffers from poor absorbance of orange light by the so-called Q-band of the absorption spectrum (maximum absorption wavelength λmax = 600 nm, at which molar extinction coefficient εmax = 1.0×104 L/(mol·cm)), hindering photo-curing applications that entail long light penetration paths. Over the past decade, there has not been any competing candidate in terms of efficiency, despite a myriad of efforts in PC design. By theoretical evaluation, here we rationally introduce a peripheral benzo moiety on each of the pyrrole rings of ZnTPP, giving zinc tetraphenyl tetrabenzoporphyrin (ZnTPTBP). This modification not only enlarges the conjugation length of the system, but also alters the a1u occupied π molecular orbital energy level and breaks the accidental degeneracy between the a1u and a2u orbitals, which is responsible for the low absorption intensity of the Q-band. As a consequence, not only is there a pronounced hyperchromic and bathochromic effect (λmax = 655 nm and εmax = 5.2×104 L/(mol·cm)) of the Q-band, but the hyperchromic effect is achieved without increasing the intensity of the less useful, low wavelength absorption peaks of the PC. Remarkably, this strong 655 nm absorption takes advantage of deep-red (650-700 nm) light, a major component of solar light exhibiting good atmosphere penetration, exploited by the natural PC chlorophyll a as well. Compared with ZnTPP, ZnTPTBP displayed a 49% increase in PET-RAFT polymerization rate with good control, marking a significant leap in the area of photo-controlled polymerization.

On committor functions in milestoning.

As an optimal one-dimensional reaction coordinate, the committor function not only describes the probability of a trajectory initiated at a phase space point first reaching the product state before reaching the reactant state but also preserves the kinetics when utilized to run a reduced dynamics model. However, calculating the committor function in high-dimensional systems poses significant challenges. In this paper, within the framework of milestoning, exact expressions for committor functions at two levels of coarse graining are given, including committor functions of phase space point to point (CFPP) and milestone to milestone (CFMM). When combined with transition kernels obtained from trajectory analysis, these expressions can be utilized to accurately and efficiently compute the committor functions. Furthermore, based on the calculated committor functions, an adaptive algorithm is developed to gradually refine the transition state region. Finally, two model examples are employed to assess the accuracy of these different formulations of committor functions.

Topological analysis of information-theoretic quantities in density functional theory.

We have witnessed considerable research interest in the recent literature about the development and applications of quantities from the information-theoretic approach (ITA) in density functional theory. These ITA quantities are explicit density functionals, whose local distributions in real space are continuous and well-behaved. In this work, we further develop ITA by systematically analyzing the topological behavior of its four representative quantities, Shannon entropy, two forms of Fisher information, and relative Shannon entropy (also called information gain or Kullback-Leibler divergence). Our results from their topological analyses for 103 molecular systems provide new insights into bonding interactions and physiochemical properties, such as electrophilicity, nucleophilicity, acidity, and aromaticity. We also compare our results with those from the electron density, electron localization function, localized orbital locator, and Laplacian functions. Our results offer a new methodological approach and practical tool for applications that are especially promising for elucidating chemical bonding and reactivity propensity.

Dynamic Causal Modeling and Online Collaborative Forecasting of Air Quality in Hong Kong and Macao.

The Hong Kong and Macao Special Administrative Regions, situated within China's Guangdong-Hong Kong-Macao Greater Bay Area, significantly influence and are impacted by their air quality conditions. Rapid urbanization, high population density, and air pollution from diverse factors present challenges, making the health of the atmospheric environment in these regions a research focal point. This study offers three key contributions: (1) It applied an interpretable dynamic Bayesian network (DBN) to construct a dynamic causal model of air quality in Hong Kong and Macao, amidst complex, unstable, multi-dimensional, and uncertain factors over time. (2) It investigated the dynamic interaction between meteorology and air quality sub-networks, and both qualitatively and quantitatively identified, evaluated, and understood the causal relationships between air pollutants and their determinants. (3) It facilitated an online collaborative forecast of air pollutant concentrations, enabling pollution warnings. The findings proposed that a DBN-based dynamic causal model can effectively explain and manage complex atmospheric environmental systems in Hong Kong and Macao. This method offers crucial insights for decision-making and the management of atmospheric environments not only in these regions but also for neighboring cities and regions with similar geographical contexts.

[Correlation between frailty and erectile dysfunction in elderly males].

OBJECTIVE: To investigate the correlation of frailty with ED in Chinese elderly men. METHODS: This community-based study was conducted with a sample of 258 Chinese men aged 60 to 83 years old in Fuyang City, Anhui Province. All the participants completed a standard questionnaire on demographics, lifestyle, underlying diseases and medical and sexual histories. They also scored on the Chinese version of Tilburg Frailty Indicator (TFI) and International Index of Erectile Function-5 (IIEF-5). RESULTS: The incidence rates of ED and frailty in the elderly men were 85.27% and 75.58%, respectively. The ED patients, compared with the non-ED males, had a significantly older age (ï¼»71.25 ± 5.83ï¼½ vs ï¼»66.92 ± 5.44ï¼½ yr, P < 0.01) and higher body mass index (ï¼»24.37 ± 3.31ï¼½ vs ï¼»23.35 ± 2.97ï¼½ kg/m 2, P < 0.05), incidence of diabetes mellitus (38.0% vs 19.2%, P < 0.05) and TFI scores (8.61 ± 4.29 vs 5.95 ± 4.36, P < 0.05), but lower education and frequency of irregular intercourse (less than once a week) (all P<0.05). Multivariate analysis indicated that diabetes (OR：3.292，95% CI：1.236－8.768), irregular intercourse (OR：2.425，95% CI：1.114－5.279), and scores of frailty (OR：4.502，95% CI：1.905－10.640) were regarded as independent risk factors for ED (all P < 0.05). CONCLUSION: There is a strong correlation between ED and frailty in elderly men. Sexual health care for elderly ED patients should be more focused on the multidimensional assessment and treatment of senile frailty.

NAC-TDDFT: Time-Dependent Density Functional Theory for Nonadiabatic Couplings.

First-order nonadiabatic coupling (NAC) matrix elements (fo-NACMEs) are the basic quantities in theoretical descriptions of electronically nonadiabatic processes that are ubiquitous in molecular physics and chemistry. Given the large size of systems of chemical interests, time-dependent density functional theory (TDDFT) is usually the first choice of methods. However, the lack of many-electron wave functions in TDDFT renders the formulation of NAC-TDDFT for fo-NACMEs conceptually difficult. Because of this, various variants of NAC-TDDFT have been proposed in the literature from different standing points, including the Hellmann-Feynman-like expression and auxiliary/pseudo-wave function (AWF)-, equation-of-motion (EOM)-, and time-dependent perturbation theory (TDPT)-based formulations. Based on critical analyses, the following conclusions are made here: (1) The Hellmann-Feynman-like expression, which is rooted in exact wave function theory, is hardly useful due to huge demand on basis sets. (2) Although most popular, the AWF variants of NAC-TDDFT are not theoretically founded and become ambiguous particularly for the fo-NACMEs between two excited states, although they do agree with the EOM and TDPT variants under the Tamm-Dancoff approximation. (3) The TDPT variant of NAC-TDDFT is theoretically most rigorous but suffers from numerical instabilities on the one hand and does not differ to a significant extent from the EOM variant on the other hand. (4) As such, the EOM variant of NAC-TDDFT for the fo-NACMEs between the ground and excited states and between two excited states is solely the right choice in practice. These formal analyses are fully supported by numerical experimentations, taking azulene as a showcase. The proper implementation of the EOM variant of NAC-TDDFT is also highlighted, showing that the fo-NACMEs between the ground and excited states and between two excited states are computationally very much the same as the analytic energy gradients of DFT and TDDFT, respectively. Possible future developments of the EOM variant of NAC-TDDFT are also highlighted. Its extensions to spin-adapted open-shell TDDFT and proper treatment of spin-orbit couplings (which are another source of force for electronically nonadiabatic processes) are particularly warranted in the near future.

Integrative analysis identifies CXCL11 as an immune-related prognostic biomarker correlated with cell proliferation and immune infiltration in multiple myeloma microenvironment.

PURPOSE: The interaction between tumor cells and tumor microenvironment (TME) has an important impact on progression and prognosis of multiple myeloma (MM), and has been proven to be promising therapeutic targets. This study intended to explore the relationship between TME and prognosis and identify valuable biomarkers of MM. METHODS: The transcriptomic and clinical information of MM retrieved from the Gene Expression Omnibus (GEO) were used to establish the model. The curve of Kaplan-Meier survival and the time-dependent receiver operating characteristic (ROC) were used to appraise the predictive ability. A nomogram was established for clinical application. Furthermore, the CIBERSORT algorithm was used to investigate the relation between IRGPI with the infiltration of immune cells. We also used histology, as well as in vitro and in vivo experiments to validate these findings. RESULTS: The results demonstrated an immune-related gene-based prognostic index (IRGPI) combined with clinical information. Patients were separated into high- and low-risk groups based on risk score, which had significantly difference in survival status and immune infiltrations. Furthermore, we identified CXCL11 as a key factor, which positively promotes the progression of MM and correlate with macrophage M2-like polarization and tumor immune cells infiltration. CONCLUSION: Our findings suggest the IRGPI significantly demonstrate the differential prognosis and prediction of immune cells infiltration. It provides some insights into the complex interaction between myeloma tumor cells and the TME, as well as in the development of a novel biomarker target for anti-MM therapy.

Rapid and precise identification of bloodstream infections using a pre-treatment protocol combined with high-throughput multiplex genetic detection system.

BACKGROUND: Bloodstream infection (BSI) is a life-threatening condition with high morbidity and mortality rates worldwide. Early diagnosis of BSI is critical to avoid the unnecessary application of antimicrobial agents and for proper treatment. However, the current standard methods based on blood culture are time-consuming, thus failing to provide a timely etiological diagnosis of BSI, and common PCR-based detection might be inhibited by matrix components. METHODS: The current study explored an integrated pre-analytical treatment protocol for whole blood samples, wherein pathogens are enriched and purified by incubation and concentration, and inhibitors are inactivated and removed. Further, this study developed and evaluated a novel high-throughput multiplex genetic detection system (HMGS) to detect 24 of the most clinically prevalent BSI pathogens in blood culture samples and pre-treated whole blood samples. The specificity and sensitivity were evaluated using related reference strains and quantified bacterial/fungal suspensions. The clinical utility of BSI-HMGS combined with the pre-analytical treatment protocol was verified using blood cultures and whole blood samples. RESULTS: The combined pre-treatment protocol and BSI-HMGS was highly specific for target pathogens and possessed a low detection limit for clinical whole blood samples. The pre-treatment protocol could deplete the PCR inhibitors effectively. For blood culture samples, the current method showed 100.0% negative percent agreements and > 87.5% positive percent agreements compared to the reference results based on blood culture findings. For whole blood samples, the current method showed 100.0% negative percent agreements and > 80.0% positive percent agreements compared to the reference results for most pathogens. The turnaround time was ≤ 8 h, and all the procedures could be conducted in a general clinical laboratory. CONCLUSION: The BSI-HMGS combined with the pre-treatment protocol was a practical and promising method for early and precise detection of BSIs, especially for areas without access to advanced medical facilities.

Self-adaptive real-time time-dependent density functional theory for x-ray absorptions.

Real-time time-dependent density functional theory (RT-TDDFT) can, in principle, access the whole absorption spectrum of a many-electron system exposed to a narrow pulse. However, this requires an accurate and efficient propagator for the numerical integration of the time-dependent Kohn-Sham equation. While a low-order time propagator is already sufficient for the low-lying valence absorption spectra, it is no longer the case for the x-ray absorption spectroscopy (XAS) of systems composed even only of light elements, for which the use of a high-order propagator is indispensable. It is then crucial to choose a largest possible time step and a shortest possible simulation time so as to minimize the computational cost. To this end, we propose here a robust AutoPST approach to determine automatically (Auto) the propagator (P), step (S), and time (T) for relativistic RT-TDDFT simulations of XAS.

Identification of a prognostic metabolic gene signature in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a clinically diverse disease. Given the numerous genetic mutations and variations associated with it, a prognostic gene signature that can be related to the overall survival (OS) is a clinical implication. We used the mRNA expression profiles and clinicopathological data of patients with DLBCL from the Gene Expression Omnibus (GEO) database to identify a metabolism-related gene signature. Using LASSO regression analysis, a novel 13-metabolic gene signature was identified to evaluate prognosis. The information gathered was used to construct the nomogram model to improve risk stratification and quantify risk factors for individual patients. We performed gene set enrichment analysis to identify the enriched signalling axes to further understand the underlying biological pathways. The receiver operating characteristic (ROC) curve revealed a satisfactory performance in the training cohorts. The model also showed clinical benefit when compared to the standard prognostic factors (P < .05) in validation cohorts. This study aimed to combine metabolic dysregulation with clinical features of patients with DLBCL to generate a prognostic model that might not only indicate the value of the metabolic microenvironment for prognostic stratification but also improve the decision-making during individual therapy.

Establishment of a prognostic ferroptosis-related gene profile in acute myeloid leukaemia.

Acute myeloid leukaemia (AML) is a heterogeneous disease with a difficult to predict prognosis. Ferroptosis, an iron-induced programmed cell death, is a promising target for cancer therapy. Nevertheless, not much is known about the relationship between ferroptosis-related genes and AML prognosis. Herein, we retrieved RNA profile and corresponding clinical data of AML patients from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Univariate Cox analysis was employed to identify ferroptosis-related genes significantly associated with AML prognosis. Next, the least absolute shrinkage and selection operator (LASSO) regression was employed to establish a prognostic ferroptosis-related gene profile. 12 ferroptosis-related genes were screened to generate a prognostic model, which stratified patients into a low- (LR) or high-risk (HR) group. Using Kaplan-Meier analysis, we demonstrated that the LR patients exhibited better prognosis than HR patients. Moreover, receiver operating characteristic (ROC) curve analysis confirmed that the prognostic model showed good predictability. Functional enrichment analysis indicated that the infiltration of regulatory T cells (Treg) differed vastly between the LR and HR groups. Our prognostic model can offer guidance into the accurate prediction of AML prognosis and selection of personalized therapy in clinical practice.

E3 ubiquitin ligase HECW1 promotes the metastasis of non-small cell lung cancer cells through mediating the ubiquitination of Smad4.

Lung cancer is the leading cause of cancer-related death globally. Ubiquitin modification plays a crucial role in the regulation of gene expression, and is closely associated with cancer pathogenesis. The aim of our study was to clarify the role and mechanisms of action for HECT, C2 and WW domain containing E3 ubiquitin protein ligase 1 (HECW1) in non-small cell lung cancer (NSCLC). Herein, we demonstrate that the expression of HECW1 was significantly increased in NSCLC cell lines and tissues. Upregulation of HECW1 markedly enhanced the proliferation of NSCLC cells, whereas downregulation of HECW1 significantly inhibited proliferation. Moreover, the expression levels of HECW1 positively correlated with the migration and invasiveness of NSCLC cells. Upregulation or downregulation of HECW1 only affected the protein expression levels of SMAD family member 4 (Smad4), but had no effect on the mRNA expression levels. Furthermore, after treatment with MG-132, the relative protein level of Smad4 significantly increased in NSCLC cells. HECW1 promoted the proliferation, migration, and invasiveness of NSCLC cells by inducing the ubiquitination and degradation of Smad4, thus our data provide a novel target for NSCLC treatment.

Diffuse large B cell lymphoma-derived extracellular vesicles educate macrophages to promote tumours progression by increasing PGC-1ß.

Tumour-associated macrophages (TAMs) comprise an important part of the tumour microenvironment and play a key role in malignant tumours progression. Tumour-derived extracellular vesicles (EVs) modulated TAMs polarization and reprogrammed TAMs to influence the progression of various tumours. Here, we hypothesized that diffuse large B cell lymphoma (DLBCL)-derived EVs can regulate macrophages polarization and thus contribute to tumour progression. Our results demonstrated that EVs, released from DLBCL, augment the M2 polarization effects of macrophages. Moreover, conditional medium derived from macrophages by DLBCL-derived EVs stimulation revealed the superior effects of promoting tumour proliferation, migration and invasion. Further analysis demonstrated that DLBCL-derived EVs regulated the metabolism of macrophages by increasing the expression of PGC-1ß protein, thereby reprogramming the macrophage phenotype of promoting tumour progression. In conclusion, our findings signify that the DLBCL-derived EVs mediated the increasing of functional PGC-1ß protein in macrophages to promote the tumour progression.

Prognostic value of platelet recovery degree before and after achieving minimal residual disease negative complete remission in acute myeloid leukemia patients.

BACKGROUND: Risk stratification and prognosis prediction of acute myeloid leukemia (AML) are largely dependent on pre-treatment information. However, post-treatment data also provides much useful information. In this retrospective study, we explored whether the level of blood count recovery before and after the first minimal residual disease (MRD) negative complete remission (CR) is relevant to clinical outcomes of AML patients. METHODS: For each included patient, peripheral platelet counts were measured on the day before initial treatment (PLTpre), whereas platelet peak values (PLTpeak) were recorded after marrow recovery following the chemotherapy course inducing the first MRD-negative CR. The difference (DPLT) between these two values (DPLT = PLTpeak-PLTpre) was calculated. X-tile software was utilized to establish the optimal cut-point for DPLT, which was expected to distinguish CR patients with different clinical outcomes. A cross validation analysis was conducted to confirm the robustness of the established cut-point. The results were further tested by a Cox multivariate analysis. RESULTS: The optimal cut-point of DPLT was determined as 212 × 109/L. Patients in high DPLT group were observed to have a significantly better PFS (p = 0.016) and a better OS (without statistical significance, p = 0.106). Cox multivariate analysis showed that higher DPLT was associated with longer PFS (HR = 2.894, 95% CI: 1.320-6.345, p = 0.008) and longer OS (HR = 3.077, 95% CI: 1.130-8.376, p = 0.028). CONCLUSION: Platelet recovery degree before and after achieving MRD-negative CR (DPLT) is a potential predictor of clinical outcomes in CR patients. Higher DPLT value is associated with longer PFS and OS. Our findings may help to develop simple methods for AML prognosis evaluation.